Metabolic profiling in children with autism spectrum disorder with and without mental regression: preliminary results from a cross-sectional case-control study

Etiologic Evaluation of Children with Autism Spectrum Disorder

Autism spectrum disorder (ASD) is clinically and etiologically heterogeneous. A causal genetic variant can be identified in approximately 20% to 25% of affected individuals with current clinical genetic testing, and all patients with an ASD diagnosis should be offered genetic etiologic evaluation. We suggest that exome sequencing with copy number variant coverage should be the first-line etiologic evaluation for ASD. Neuroimaging, neurophysiologic, metabolic, and other biochemical evaluations can provide insight into the pathophysiology of ASD but should be recommended in the appropriate clinical circumstances.

Genomic insights and advanced machine learning: characterizing autism spectrum disorder biomarkers and genetic interactions

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by altered brain connectivity and function. In this study, we employed advanced bioinformatics and explainable AI to analyze gene expression associated with ASD, using data from five GEO datasets. Among 351 neurotypical controls and 358 individuals with autism, we identified 3,339 Differentially Expressed Genes (DEGs) with an adjusted p-value (≤ 0.05). A subsequent meta-analysis pinpointed 342 DEGs (adjusted p-value ≤ 0.001), including 19 upregulated and 10 down-regulated genes across all datasets. Shared genes, pathogenic single nucleotide polymorphisms (SNPs), chromosomal positions, and their impact on biological pathways were examined. We identified potential biomarkers (HOXB3, NR2F2, MAPK8IP3, PIGT, SEMA4D, and SSH1) through text mining, meriting further investigation. Additionally, ‎we shed light on the roles of RPS4Y1 and KDM5D genes in neurogenesis and neurodevelopment. Our analysis detected 1,286 SNPs linked to ASD-related conditions, of which 14 high-risk SNPs were located on chromosomes 10 and X. We highlighted potential missense SNPs associated with FGFR inhibitors, suggesting that it may serve as a promising biomarker for responsiveness to targeted therapies. Our explainable AI model identified the MID2 gene as a potential ASD biomarker. This research unveils vital genes and potential biomarkers, providing a foundation for novel gene discovery in complex diseases.

Using urine FTIR spectra to screen autism spectrum disorder

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder caused by multiple factors, lacking clear biomarkers. Diagnosing ASD still relies on behavioural and developmental signs and usually requires lengthy observation periods, all of which are demanding for both clinicians and parents. Although many studies have revealed valuable knowledge in this field, no clearly defined, practical, and widely acceptable diagnostic tool exists. In this study, 26 children with ASD (ASD+), aged 3-5 years, and 26 sex and age-matched controls are studied to investigate the diagnostic potential of the Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy. The urine FTIR spectrum results show a downward trend in the 3000-2600/cm region for ASD+ children when compared to the typically developing (TD) children of the same age. The average area of this region is 25% less in ASD+ level 3 children, 29% less in ASD+ level 2 children, and 16% less in ASD+ level 1 children compared to that of the TD children. Principal component analysis was applied to the two groups using the entire spectrum window and five peaks were identified for further analysis. The correlation between the peaks and natural urine components is validated by artificial urine solutions. Less-than-normal levels of uric acid, phosphate groups, and ammonium ([Formula: see text]) can be listed as probable causes. This study shows that ATR-FTIR can serve as a practical and non-invasive method to screen ASD using the high-frequency region of the urine spectrum.

Effect of Regular Consumption of a Miraculin-Based Food Supplement on Taste Perception and Nutritional Status in Malnourished Cancer Patients: A Triple-Blind, Randomized, Placebo-Controlled Clinical Trial-CLINMIR Pilot Protocol

Taste disorders are common among cancer patients undergoing chemotherapy, with a prevalence ranging from 20% to 86%, persisting throughout treatment. This condition leads to reduced food consumption, increasing the risk of malnutrition. Malnutrition is associated not only with worse treatment efficacy and poor disease prognosis but also with reduced functional status and quality of life. The fruit of Synsepalum dulcificum (Daniell), commonly known as miracle berry or miracle fruit, contains miraculin, a taste-modifying protein with profound effects on taste perception. The CLINMIR Protocol is a triple-blind, randomized, placebo-controlled clinical trial designed to evaluate the regular consumption of a food supplement containing a miraculin-based novel food, dried miracle berry (DMB), on the taste perception (measured through electrogustometry) and nutritional status (evaluated through the GLIM Criteria) of malnourished cancer patients under active antineoplastic treatment. To this end, a pilot study was designed with 30 randomized patients divided into three study arms (150 mg DMB + 150 mg freeze-dried strawberries, 300 mg DMB, or placebo) for three months. Throughout the five main visits, an exhaustive assessment of different parameters susceptible to improvement through regular consumption of the miraculin-based food supplement will be conducted, including electrical and chemical taste perception, smell perception, nutritional and morphofunctional assessment, diet, quality of life, the fatty acid profile of erythrocytes, levels of inflammatory and cancer-associated cytokines, oxidative stress, antioxidant defense system, plasma metabolomics, and saliva and stool microbiota. The primary anticipated result is that malnourished cancer patients with taste distortion who consume the miraculin-based food supplement will report an improvement in food taste perception. This improvement translates into increased food intake, thereby ameliorating their nutritional status and mitigating associated risks. Additionally, the study aims to pinpoint the optimal dosage that provides maximal benefits. The protocol adheres to the SPIRIT 2013 Statement, which provides evidence-based recommendations and is widely endorsed as an international standard for trial protocols. The clinical trial protocol has been registered at the platform for Clinical Trials (NCT05486260).

Metabolomic biomarkers in autism: identification of complex dysregulations of cellular bioenergetics

Autism Spectrum Disorder (ASD or autism) is a phenotypically and etiologically heterogeneous condition. Identifying biomarkers of clinically significant metabolic subtypes of autism could improve understanding of its underlying pathophysiology and potentially lead to more targeted interventions. We hypothesized that the application of metabolite-based biomarker techniques using decision thresholds derived from quantitative measurements could identify autism-associated subpopulations. Metabolomic profiling was carried out in a case-control study of 499 autistic and 209 typically developing (TYP) children, ages 18-48 months, enrolled in the Children's Autism Metabolome Project (CAMP; ClinicalTrials.gov Identifier: NCT02548442). Fifty-four metabolites, associated with amino acid, organic acid, acylcarnitine and purine metabolism as well as microbiome-associated metabolites, were quantified using liquid chromatography-tandem mass spectrometry. Using quantitative thresholds, the concentrations of 4 metabolites and 149 ratios of metabolites were identified as biomarkers, each identifying subpopulations of 4.5-11% of the CAMP autistic population. A subset of 42 biomarkers could identify CAMP autistic individuals with 72% sensitivity and 90% specificity. Many participants were identified by several metabolic biomarkers. Using hierarchical clustering, 30 clusters of biomarkers were created based on participants' biomarker profiles. Metabolic changes associated with the clusters suggest that altered regulation of cellular metabolism, especially of mitochondrial bioenergetics, were common metabolic phenotypes in this cohort of autistic participants. Autism severity and cognitive and developmental impairment were associated with increased lactate, many lactate containing ratios, and the number of biomarker clusters a participant displayed. These studies provide evidence that metabolic phenotyping is feasible and that defined autistic subgroups can lead to enhanced understanding of the underlying pathophysiology and potentially suggest pathways for targeted metabolic treatments.

Metabolomics: Perspectives on Clinical Employment in Autism Spectrum Disorder

Precision medicine is imminent, and metabolomics is one of the main actors on stage. We summarize and discuss the current literature on the clinical application of metabolomic techniques as a possible tool to improve early diagnosis of autism spectrum disorder (ASD), to define clinical phenotypes and to identify co-occurring medical conditions. A review of the current literature was carried out after PubMed, Medline and Google Scholar were consulted. A total of 37 articles published in the period 2010-2022 was included. Selected studies involve as a whole 2079 individuals diagnosed with ASD (1625 males, 394 females; mean age of 10, 9 years), 51 with other psychiatric comorbidities (developmental delays), 182 at-risk individuals (siblings, those with genetic conditions) and 1530 healthy controls (TD). Metabolomics, reflecting the interplay between genetics and environment, represents an innovative and promising technique to approach ASD. The metabotype may mirror the clinical heterogeneity of an autistic condition; several metabolites can be expressions of dysregulated metabolic pathways thus liable of leading to clinical profiles. However, the employment of metabolomic analyses in clinical practice is far from being introduced, which means there is a need for further studies for the full transition of metabolomics from clinical research to clinical diagnostic routine.

Dysregulation of Amino Acid Transporters in a Rat Model of TLR7-Mediated Maternal Immune Activation

Maternal immune activation (MIA) during pregnancy is linked to neurodevelopmental disorders in humans. Similarly, the TLR7 agonist imiquimod alters neurodevelopment in rodents. While the mechanisms underlying MIA-mediated neurodevelopmental changes are unknown, they could involve dysregulation of amino acid transporters essential for neurodevelopment. Therefore, we sought to determine the nature of such transporter changes in both imiquimod-treated rats and human placentas during infection. Pregnant rats received imiquimod on gestational day (GD)14. Transporter expression was measured in placentas and fetal brains via qPCR (GD14.5) and immunoblotting (GD16). To monitor function, fetal brain amino acid levels were measured by HPLC on GD16. Gene expression in the cortex of female fetal brains was further examined by RNAseq on GD19. In human placentas, suspected active infection was associated with decreased ASCT1 and SNAT2 protein expression. Similarly, in imiquimod-treated rats, ASCT1 and SNAT2 protein was also decreased in male placentas, while EAAT2 was decreased in female placentas. CAT3 was increased in female fetal brains. Consistent with this, imiquimod altered amino acid levels in fetal brains, while RNAseq demonstrated changes in expression of several genes implicated in autism. Thus, imiquimod alters amino acid transporter levels in pregnant rats, and similar changes occur in human placentas during active infection. This suggests that changes in expression of amino acid transporters may contribute to effects mediated by MIA toward altered neurodevelopment.

Investigating the Urinary Metabolome in the First Year of Life and Its Association with Later Diagnosis of Autism Spectrum Disorder or Non-Typical Neurodevelopment in the MARBLES Study

Developmental disabilities are often associated with alterations in metabolism. However, it remains unknown how early these metabolic issues may arise. This study included a subset of children from the Markers of Autism Risks in Babies-Learning Early Signs (MARBLES) prospective cohort study. In this analysis, 109 urine samples collected at 3, 6, and/or 12 months of age from 70 children with a family history of ASD who went on to develop autism spectrum disorder (ASD n = 17), non-typical development (Non-TD n = 11), or typical development (TD n = 42) were investigated by nuclear magnetic resonance (NMR) spectroscopy to measure urinary metabolites. Multivariate principal component analysis and a generalized estimating equation were performed with the objective of exploring the associations between urinary metabolite levels in the first year of life and later adverse neurodevelopment. We found that children who were later diagnosed with ASD tended to have decreased urinary dimethylamine, guanidoacetate, hippurate, and serine, while children who were later diagnosed with Non-TD tended to have elevated urinary ethanolamine and hypoxanthine but lower methionine and homovanillate. Children later diagnosed with ASD or Non-TD both tended to have decreased urinary 3-aminoisobutyrate. Our results suggest subtle alterations in one-carbon metabolism, gut-microbial co-metabolism, and neurotransmitter precursors observed in the first year of life may be associated with later adverse neurodevelopment.

Prostaglandin I2 suppresses the development of gut-brain axis disorder in irritable bowel syndrome in rats

In this study, we attempted to clarify a role of prostaglandin (PG) I₂ and its specific receptor, IP in the pathogenesis of irritable bowel syndrome (IBS) using a maternal separation (MS)-induced IBS model. Administration of beraprost (BPS), a specific IP agonist, improved visceral hypersensitivity and depressive state with decreased serum CRF level in the IBS rats. To clarify the mechanism of the effect of BPS, we performed serum metabolome analysis and 1-methylnicotinamide (1-MNA) was identified as a possible candidate for a clue metabolite of pathogenesis of IBS. The serum 1-MNA levels revealed inverse correlation to the level of visceral sensitivity, and positive correlation to a depression marker, immobilizing time. Administration of 1-MNA induced visceral hypersensitivity and depression with increased levels of serum CRF. Since fecal 1-MNA is known for a marker of dysbiosis, we examined the composition of fecal microbiota by T-RFLP analysis. The proportion of clostridium cluster XI, XIVa and XVIII was significantly changed in MS-induced IBS rats treated with BPS. Fecal microbiota transplant of BPS-treated rats improved visceral hypersensitivity and depression in IBS rats. These results suggest for the first time that PGI₂-IP signaling plays an important role in IBS phenotypes such as visceral hypersensitivity and depressive state. BPS modified microbiota, thereby inhibition of 1-MNA-CRF pathway, followed by improvement of MS-induced IBS phenotype. These results suggest that the PGI₂-IP signaling could be considered to be a therapeutic option for IBS.

Intestinal Barrier Dysfunction and Microbiota–Gut–Brain Axis: Possible Implications in the Pathogenesis and Treatment of Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with multifactorial etiology, characterized by impairment in two main functional areas: (1) communication and social interactions, and (2) skills, interests and activities. ASD patients often suffer from gastrointestinal symptoms associated with dysbiotic states and a “leaky gut.” A key role in the pathogenesis of ASD has been attributed to the gut microbiota, as it influences central nervous system development and neuropsychological and gastrointestinal homeostasis through the microbiota–gut–brain axis. A state of dysbiosis with a reduction in the Bacteroidetes/Firmicutes ratio and Bacteroidetes level and other imbalances is common in ASD. In recent decades, many authors have tried to study and identify the microbial signature of ASD through in vivo and ex vivo studies. In this regard, the advent of metabolomics has also been of great help. Based on these data, several therapeutic strategies, primarily the use of probiotics, are investigated to improve the symptoms of ASD through the modulation of the microbiota. However, although the results are promising, the heterogeneity of the studies precludes concrete evidence. The aim of this review is to explore the role of intestinal barrier dysfunction, the gut–brain axis and microbiota alterations in ASD and the possible role of probiotic supplementation in these patients.

Neuroinflammation, Energy and Sphingolipid Metabolism Biomarkers Are Revealed by Metabolic Modeling of Autistic Brains

Autism spectrum disorders (ASD) are a heterogeneous group of neurodevelopmental disorders generally characterized by repetitive behaviors and difficulties in communication and social behavior. Despite its heterogeneous nature, several metabolic dysregulations are prevalent in individuals with ASD. This work aims to understand ASD brain metabolism by constructing an ASD-specific prefrontal cortex genome-scale metabolic model (GEM) using transcriptomics data to decipher novel neuroinflammatory biomarkers. The healthy and ASD-specific models are compared via uniform sampling to identify ASD-exclusive metabolic features. Noticeably, the results of our simulations and those found in the literature are comparable, supporting the accuracy of our reconstructed ASD model. We identified that several oxidative stress, mitochondrial dysfunction, and inflammatory markers are elevated in ASD. While oxidative phosphorylation fluxes were similar for healthy and ASD-specific models, and the fluxes through the pathway were nearly undisturbed, the tricarboxylic acid (TCA) fluxes indicated disruptions in the pathway. Similarly, the secretions of mitochondrial dysfunction markers such as pyruvate are found to be higher, as well as the activities of oxidative stress marker enzymes like alanine and aspartate aminotransferases (ALT and AST) and glutathione-disulfide reductase (GSR). We also detected abnormalities in the sphingolipid metabolism, which has been implicated in many inflammatory and immune processes, but its relationship with ASD has not been thoroughly explored in the existing literature. We suggest that important sphingolipid metabolites, such as sphingosine-1-phosphate (S1P), ceramide, and glucosylceramide, may be promising biomarkers for the diagnosis of ASD and provide an opportunity for the adoption of early intervention for young children.

Glutamatergic synapse in autism: a complex story for a complex disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder whose pathophysiological mechanisms are still unclear. Hypotheses suggest a role for glutamate dysfunctions in ASD development, but clinical studies investigating brain and peripheral glutamate levels showed heterogenous results leading to hypo- and hyper-glutamatergic hypotheses of ASD. Recently, studies proposed the implication of elevated mGluR5 densities in brain areas in the pathophysiology of ASD. Thus, our objective was to characterize glutamate dysfunctions in adult subjects with ASD by quantifying (1) glutamate levels in the cingulate cortex and periphery using proton magnetic resonance spectroscopy and metabolomics, and (2) mGluR5 brain density in this population and in a validated animal model of ASD (prenatal exposure to valproate) at developmental stages corresponding to childhood and adolescence in humans using positron emission tomography. No modifications in cingulate Glu levels were observed between individuals with ASD and controls further supporting the difficulty to evaluate modifications in excitatory transmission using spectroscopy in this population, and the complexity of its glutamate-related changes. Our imaging results showed an overall increased density in mGluR5 in adults with ASD, that was only observed mostly subcortically in adolescent male rats prenatally exposed to valproic acid, and not detected in the stage corresponding to childhood in the same animals. This suggest that clinical changes in mGluR5 density could reflect the adaptation of the glutamatergic dysfunctions occurring earlier rather than being key to the pathophysiology of ASD.

NMR-Based Metabolomics of Rat Hippocampus, Serum, and Urine in Two Models of Autism

Autism spectrum disorders (ASDs) are increasingly diagnosed as developmental disabilities of unclear etiology related to genetic, epigenetic, or environmental factors. The diagnosis of ASD in children is based on the recognition of typical behavioral symptoms, while no reliable biomarkers are available. Rats in whom ASD-like symptoms are due to maternal administration of the teratogenic drugs valproate or thalidomide on critical day 11 of pregnancy are widely used models in autism research. The present studies, aimed at detecting changes in the levels of hydrophilic and hydrophobic metabolites, were carried out on 1-month-old rats belonging to the abovementioned two ASD models and on a control group. Analysis of both hydrophilic and hydrophobic metabolite levels gives a broader view of possible mechanisms involved in the pathogenesis of autism. Hippocampal proton magnetic resonance (MRS) spectroscopy and ex vivo nuclear magnetic resonance (NMR) analysis of serum and urine samples were used. The results were analyzed using advanced statistical tests. Both the results of our present MRS studies of the hippocampus and of the NMR studies of body fluids in both ASD models, particularly from the THAL model, appeared to be consistent with previously published NMR results of hippocampal homogenates and data from the literature on autistic children. We detected symptoms of disturbances in neurotransmitter metabolism, energy deficit, and oxidative stress, as well as intestinal malfunction, which shed light on the pathogenesis of ASD and could be used for diagnostic purposes. These results confirm the usefulness of the noninvasive techniques used in ASD studies.

Association between EEG Paroxysmal Abnormalities and Levels of Plasma Amino Acids and Urinary Organic Acids in Children with Autism Spectrum Disorder

Abnormalities in the plasma amino acid and/or urinary organic acid profile have been reported in autism spectrum disorder (ASD). An imbalance between excitatory and inhibitory neuronal activity has been proposed as a mechanism to explain dysfunctional brain networks in ASD, as also suggested by the increased risk of epilepsy in this disorder. This study explored the possible association between presence of EEG paroxysmal abnormalities and the metabolic profile of plasma amino acids and urinary organic acids in children with ASD. In a sample of 55 children with ASD (81.8% male, mean age 53.67 months), EEGs were recorded, and 24 plasma amino acids and 56 urinary organic acids analyzed. EEG epileptiform discharges were found in 36 (65%) children. A LASSO regression, adjusted by age and sex, was applied to evaluate the association of plasma amino acids and urinary organic acids profiles with the presence of EEG epileptiform discharges. Plasma levels of threonine (THR) (coefficient = -0.02, p = 0.04) and urinary concentration of 3-Hydroxy-3-Methylglutaric acid (HMGA) (coefficient = 0.04, p = 0.02) were found to be associated with the presence of epileptiform discharges. These results suggest that altered redox mechanisms might be linked to epileptiform brain activity in ASD.

Alteration of the Intestinal Permeability Are Reflected by Changes in the Urine Metabolome of Young Autistic Children: Preliminary Results

Several metabolomics-based studies have provided evidence that autistic subjects might share metabolic abnormalities with gut microbiota dysbiosis and alterations in gut mucosal permeability. Our aims were to explore the most relevant metabolic perturbations in a group of autistic children, compared with their healthy siblings, and to investigate whether the increased intestinal permeability may be mirrored by specific metabolic perturbations. We enrolled 13 autistic children and 14 unaffected siblings aged 2–12 years; the evaluation of the intestinal permeability was estimated by the lactulose:mannitol test. The urine metabolome was investigated by proton nuclear magnetic resonance (1H-NMR) spectroscopy. The lactulose:mannitol test unveiled two autistic children with altered intestinal permeability. Nine metabolites significantly discriminated the urine metabolome of autistic children from that of their unaffected siblings; however, in the autistic children with increased permeability, four additional metabolites—namely, fucose, phenylacetylglycine, nicotinurate, and 1-methyl-nicotinamide, strongly discriminated their urine metabolome from that of the remaining autistic children. Our preliminary data suggest the presence of a specific urine metabolic profile associated with the increase in intestinal permeability.

Metabolomics profiling of valproic acid-induced symptoms resembling autism spectrum disorders using 1H NMR spectral analysis in rat model

Prenatal exposure to valproic acid (VPA) has been implicated in the manifestation of autism spectrum disorder (ASD)-like behavioral and functional changes both in human and rodents including mice and rats. The objective of this study was to determine metabolomics profiling and biomarkers related to VPA-induced symptoms resembling ASD using proton nuclear magnetic resonance (1H-NMR) spectral data. VPA was administered to pregnant rats at gestation day 12.5 and effects measured subsequently in male 4-week-old offspring pups. The sociability of VPA-treated animals was significantly diminished and exhibited ASD-like behavior as evidenced by reduction of social adaptation disorder and lack of social interactions. To find biomarkers related to ASD, the following were collected prefrontal brain cortices, urine bladder and blood samples directly from heart puncture. In all samples, principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) displayed significant clustering pattern differences between control and treated groups. Valine, taurine, myo-inositol, 3-hydroxybutyrate and 1,3-dihydroxyacetone were significantly decreased in brain cortices in treated rats. Serum metabolites of glucose, creatine phosphate, lactate, glutamine and threonine were significantly increased in VPA-administered animals. Urinary metabolites of pimelate, 3-hydroxyisovalerate and valerate were significantly reduced in VPA-treated rat, whereas galactose and galactonate levels were elevated. Various metabolites were associated with mitochondrial dysfunction metabolism and central nervous system disorders. Data demonstrated that VPA-induced alterations in endogenous metabolites of serum, urine, and brain cortex which might prove useful as biomarkers for symptoms resembling ASD as a model of this disorder.

Regressive Autism Spectrum Disorder: High Levels of Total Secreted Amyloid Precursor Protein and Secreted Amyloid Precursor Protein-α in Plasma

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by social communication difficulties, repetitive behaviors, and parochial interests. Individuals with regressive ASD (RA), a unique subtype, have poor outcomes. Moreover, there are currently no validated blood-based biomarkers for ASD, hindering early diagnosis and treatment. This study was the first to examine plasma levels of total secreted amyloid precursor protein (sAPPtotal), secreted amyloid precursor protein-α (sAPPα), and secreted amyloid precursor protein-β (sAPPβ) in children diagnosed with RA (n = 23) and compare them with the levels in age-matched children with non-regressive ASD (NRA) (n = 23) and typically developing (TD) controls (n = 23). We found that sAPPtotal and sAPPα levels were significantly higher in children with RA than in children with NRA or in TD controls. In contrast, no difference was observed in sAPPβ levels. In conclusion, increased plasma levels of sAPPtotal and sAPPα may be valuable biomarkers for the early identification of ASD regression. Prospective studies will be conducted using a larger sample to further investigate these differences.

Dietary Patterns, Eating Behavior, and Nutrient Intakes of Spanish Preschool Children with Autism Spectrum Disorders

Eating behavior problems are characteristic of children with autism spectrum disorders (ASD) with a highly restricted range of food choices, which may pose an associated risk of nutritional problems. Hence, detailed knowledge of the dietary patterns (DPs) and nutrient intakes of ASD patients is necessary to carry out intervention strategies if required. The present study aimed to determine the DPs and macro-and micronutrient intakes in a sample of Spanish preschool children with ASD compared to typically developing control children. Fifty-four children with ASD (two to six years of age) diagnosed with ASD according to the Diagnostic Manual-5 criteria), and a control group of 57 typically developing children of similar ages were recruited. A validated food frequency questionnaire was used, and the intake of energy and nutrients was estimated through three non-consecutive 24-h dietary registrations. DPs were assessed using principal component analysis and hierarchical clustering analysis. Children with ASD exhibited a DP characterized by high energy and fat intakes and a low intake of vegetables and fruits. Likewise, meat intake of any type, both lean and fatty, was associated with higher consumption of fish and dietary fat. Furthermore, the increased consumption of dairy products was associated with increased consumption of cereals and pasta. In addition, they had frequent consumption of manufactured products with poor nutritional quality, e.g., beverages, sweets, snacks and bakery products. The percentages of children with ASD complying with the adequacy of nutrient intakes were higher for energy, saturated fat, calcium, and vitamin C, and lower for iron, iodine, and vitamins of group B when compared with control children. In conclusion, this study emphasizes the need to assess the DPs and nutrient intakes of children with ASD to correct their alterations and discard some potential nutritional diseases.

Profiles of urine and blood metabolomics in autism spectrum disorders

Early diagnosis and treatment for autism spectrum disorder (ASD) pose challenges. The current diagnostic approach for ASD is mainly clinical assessment of patient behaviors. Biomarkers-based identification of ASD would be useful for pediatricians. Currently, there is no specific treatment for ASD, and evidence for the efficacy of alternative treatments remains inconclusive. The prevalence of ASD is increasing, and it is becoming more urgent to find the pathogenesis of such disorder. Metabolomic studies have been used to deeply investigate the alteration of metabolic pathways, including those associated with ASD. Metabolomics is a promising tool for identifying potential biomarkers and possible pathogenesis of ASD. This review comprehensively summarizes and discusses the abnormal metabolic pathways in ASD children, as indicated by evidence from metabolomic studies in urine and blood. In addition, the targeted interventions that could correct the metabolomic profiles relating to the improvement of autistic behaviors in affected animals and humans have been included. The results revealed that the possible underlying pathophysiology of ASD were alterations of amino acids, reactive oxidative stress, neurotransmitters, and microbiota-gut-brain axis. The potential common pathways shared by animal and human studies related to the improvement of ASD symptoms after pharmacological interventions were mammalian-microbial co-metabolite, purine metabolism, and fatty acid oxidation. The content of this review may contribute to novel biomarkers for the early diagnosis of ASD and possible therapeutic paradigms.

Retinol-binding protein 4 in combination with lipids to predict the regression phenomenon of autism spectrum disorders

BACKGROUND

About 20-40 % of autistic people experience a phenomenon of regression. Retinol binding protein 4 (RBP4) plays an important role as an inflammatory neurotrophic adipokine and is a promising mediator of the fat-brain axis. Abnormal fatty acid metabolism and lipid mediators have been reported to be related to the etiological mechanism in autism, and amelioration of impaired lipid metabolism can be recognized as a treatment strategy for autism. The purpose of this study is to explore the relationship between RBP4, lipids, and the autistic regression phenomenon, and to discuss their potentials as biomarkers for the autistic regression phenomenon.

METHODS

A total of 60 autistic individuals (18 with regression phenomenon, 42 without regression phenomenon) (ASD group) and 36 healthy controls were enrolled in this case-control study. The levels of RBP4, total cholesterol (TC), high-density lipoprotein (HDLC), low-density lipoprotein (LDLC), and triglyceride (TG) were measured. Childhood Autism Rating Scale (CARS) is used to assess the severity of autism. Ethical measures were performed in compliance with the current Declaration of Helsinki and written informed consent was obtained from the parents before enrollment of the children and adolescents.

RESULTS

Compared with control subjects, autistic individuals had lower levels of TC (P = 0.007), RBP4 (P = 0.001), and HDLC (P = 0.027). The levels of RBP4 in ASD group were positively correlated with TG (r = 0.355, P = 0.005), HDLC (r = 0.257, P = 0.047), TG/TC (r = 0.376, P = 0.003) and TG/LDLC (r = 0.363, P = 0.004), and were negatively correlated with CARS (r=-0.296, P = 0.003). Further logistic regression demonstrated that decreased RBP4 concentration was associated with the presentation of the autistic regression phenomenon even after the adjustment of the potential confounding factors.

CONCLUSIONS

Serum RBP4 is associated with the autistic regression phenomenon and the severity of ASD. Further studies are needed to expound whether decreased RBP4 participates in the development of the autistic regression phenomenon.

Maternal Plasma Metabolic Profile Demarcates a Role for Neuroinflammation in Non-Typical Development of Children

Maternal and cord plasma metabolomics were used to elucidate biological pathways associated with increased diagnosis risk for autism spectrum disorders (ASD). Metabolome-wide associations were assessed in both maternal and umbilical cord plasma in relation to diagnoses of ASD and other non-typical development (Non-TD) compared to typical development (TD) in the Markers of Autism risk in Babies: Learning Early Signs (MARBLES) cohort study of children born to mothers who already have at least one child with ASD. Analyses were stratified by sample matrix type, machine mode, and annotation confidence level. Dimensionality reduction techniques were used [i.e, principal component analysis (PCA) and random subset weighted quantile sum regression (WQSRS)] to minimize the high multiple comparison burden. With WQSRS, a metabolite mixture obtained from the negative mode of maternal plasma decreased the odds of Non-TD compared to TD. These metabolites, all related to the prostaglandin pathway, underscored the relevance of neuroinflammation status. No other significant findings were observed. Dimensionality reduction strategies provided confirming evidence that a set of maternal plasma metabolites are important in distinguishing Non-TD compared to TD diagnosis. A lower risk for Non-TD was linked to anti-inflammatory elements, thereby linking neuroinflammation to detrimental brain function consistent with studies ranging from neurodevelopment to neurodegeneration.

Studying Autism Using Untargeted Metabolomics in Newborn Screening Samples

Main risk factors of autism spectrum disorder (ASD) include both genetic and non-genetic factors, especially prenatal and perinatal events. Newborn screening dried blood spot (DBS) samples have great potential for the study of early biochemical markers of disease. To study DBS strengths and limitations in the context of ASD research, we analyzed the metabolomic profiles of newborns later diagnosed with ASD. We performed LC-MS/MS-based untargeted metabolomics on DBS from 37 case-control pairs randomly selected from the iPSYCH sample. After preprocessing using MZmine 2.41, metabolites were putatively annotated using mzCloud, GNPS feature-based molecular networking, and MolNetEnhancer. A total of 4360 mass spectral features were detected, of which 150 (113 unique) could be putatively annotated at a high confidence level. Chemical structure information at a broad level could be retrieved for 1009 metabolites, covering 31 chemical classes. Although no clear distinction between cases and controls was revealed, our method covered many metabolites previously associated with ASD, suggesting that biochemical markers of ASD are present at birth and may be monitored during newborn screening. Additionally, we observed that gestational age, age at sampling, and month of birth influence the metabolomic profiles of newborn DBS, which informs us on the important confounders to address in future studies.

Comparison of the Metabolic Profiles in the Plasma and Urine Samples Between Autistic and Typically Developing Boys: A Preliminary Study

Background: Autism spectrum disorder (ASD) is defined as a pervasive developmental disorder which is caused by genetic and environmental risk factors. Besides the core behavioral symptoms, accumulated results indicate children with ASD also share some metabolic abnormalities. Objectives: To analyze the comprehensive metabolic profiles in both of the first-morning urine and plasma samples collected from the same cohort of autistic boys. Methods: In this study, 30 autistic boys and 30 tightly matched healthy control (HC) boys (age range: 2.4~6.7 years) were recruited. First-morning urine and plasma samples were collected and the liquid chromatography-mass spectrometry (LC-MS) was applied to obtain the untargeted metabolic profiles. The acquired data were processed by multivariate analysis and the screened metabolites were grouped by metabolic pathway. Results: Different discriminating metabolites were found in plasma and urine samples. Notably, taurine and catechol levels were decreased in urine but increased in plasma in the same cohort of ASD children. Enriched pathway analysis revealed that perturbations in taurine and hypotaurine metabolism, phenylalanine metabolism, and arginine and proline metabolism could be found in both of the plasma and urine samples. Conclusion: These preliminary results suggest that a series of common metabolic perturbations exist in children with ASD, and confirmed the importance to have a comprehensive analysis of the metabolites in different biological samples to reveal the full picture of the complex metabolic patterns associated with ASD. Further targeted analyses are needed to validate these results in a larger cohort.

Dissemination and analysis of the quality assurance (QA) and quality control (QC) practices of LC-MS based untargeted metabolomics practitioners

INTRODUCTION

The metabolomics quality assurance and quality control consortium (mQACC) evolved from the recognized need for a community-wide consensus on improving and systematizing quality assurance (QA) and quality control (QC) practices for untargeted metabolomics.

OBJECTIVES

In this work, we sought to identify and share the common and divergent QA and QC practices amongst mQACC members and collaborators who use liquid chromatography-mass spectrometry (LC-MS) in untargeted metabolomics.

METHODS

All authors voluntarily participated in this collaborative research project by providing the details of and insights into the QA and QC practices used in their laboratories. This sharing was enabled via a six-page questionnaire composed of over 120 questions and comment fields which was developed as part of this work and has proved the basis for ongoing mQACC outreach.

RESULTS

For QA, many laboratories reported documenting maintenance, calibration and tuning (82%); having established data storage and archival processes (71%); depositing data in public repositories (55%); having standard operating procedures (SOPs) in place for all laboratory processes (68%) and training staff on laboratory processes (55%). For QC, universal practices included using system suitability procedures (100%) and using a robust system of identification (Metabolomics Standards Initiative level 1 identification standards) for at least some of the detected compounds. Most laboratories used QC samples (>86%); used internal standards (91%); used a designated analytical acquisition template with randomized experimental samples (91%); and manually reviewed peak integration following data acquisition (86%). A minority of laboratories included technical replicates of experimental samples in their workflows (36%).

CONCLUSIONS

Although the 23 contributors were researchers with diverse and international backgrounds from academia, industry and government, they are not necessarily representative of the worldwide pool of practitioners due to the recruitment method for participants and its voluntary nature. However, both questionnaire and the findings presented here have already informed and led other data gathering efforts by mQACC at conferences and other outreach activities and will continue to evolve in order to guide discussions for recommendations of best practices within the community and to establish internationally agreed upon reporting standards. We very much welcome further feedback from readers of this article.

Proteomics and Metabolomics Approaches towards a Functional Insight onto AUTISM Spectrum Disorders: Phenotype Stratification and Biomarker Discovery

Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by behavioral alterations and currently affect about 1% of children. Significant genetic factors and mechanisms underline the causation of ASD. Indeed, many affected individuals are diagnosed with chromosomal abnormalities, submicroscopic deletions or duplications, single-gene disorders or variants. However, a range of metabolic abnormalities has been highlighted in many patients, by identifying biofluid metabolome and proteome profiles potentially usable as ASD biomarkers. Indeed, next-generation sequencing and other omics platforms, including proteomics and metabolomics, have uncovered early age disease biomarkers which may lead to novel diagnostic tools and treatment targets that may vary from patient to patient depending on the specific genomic and other omics findings. The progressive identification of new proteins and metabolites acting as biomarker candidates, combined with patient genetic and clinical data and environmental factors, including microbiota, would bring us towards advanced clinical decision support systems (CDSSs) assisted by machine learning models for advanced ASD-personalized medicine. Herein, we will discuss novel computational solutions to evaluate new proteome and metabolome ASD biomarker candidates, in terms of their recurrence in the reviewed literature and laboratory medicine feasibility. Moreover, the way to exploit CDSS, performed by artificial intelligence, is presented as an effective tool to integrate omics data to electronic health/medical records (EHR/EMR), hopefully acting as added value in the near future for the clinical management of ASD.

Untargeted Metabolomics Screen of Mid-pregnancy Maternal Serum and Autism in Offspring

Discovering pathophysiologic networks in a blood-based approach may help to generate valuable tools for early treatment or preventive measures in autism. To date targeted or untargeted metabolomics approaches to identify metabolic features and pathways affecting fetal neurodevelopment have rarely been applied to pregnancy samples, that is, an early period potentially relevant for the development of autism spectrum disorders (ASD). We conducted a population-based study relying on autism diagnoses retrieved from California Department of Developmental Services record. After linking cases to and sampling controls from birth certificates, we retrieved stored maternal mid-pregnancy serum samples collected as part of the California Prenatal Screening Program from the California Biobank for children born 2004 to 2010 in the central valley of California. We retrieved serum for 52 mothers whose children developed autism and 62 population controls originally selected from all eligible children matched by birth year and child's sex. Also, we required that these mothers were relatively low or unexposed to air pollution and select pesticides during early pregnancy. We identified differences in metabolite levels in several metabolic pathways, including glycosphingolipid biosynthesis and metabolism, N-glycan and pyrimidine metabolism, bile acid pathways and, importantly, C21-steroid hormone biosynthesis and metabolism. Disturbances in these pathways have been shown to be relevant for neurodevelopment in rare genetic syndromes or implicated in previous studies of autism. This study provides new insight into maternal mid-pregnancy metabolic features possibly related to the development of autism and an incentive to explore whether these pathways and metabolites are useful for early diagnosis, treatment, or prevention. LAY SUMMARY: This study found that in mid-pregnancy the blood of mothers who give birth to a child that develops autism has some characteristic features that are different from those of blood samples taken from control mothers. These features are related to biologic mechanisms that can affect fetal brain development. In the future, these insights may help identify biomarkers for early autism diagnosis and treatment or preventive measures. Autism Res 2020, 13: 1258-1269. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.

Emerging proteomic approaches to identify the underlying pathophysiology of neurodevelopmental and neurodegenerative disorders

Proteomics is the large-scale study of the total protein content and their overall function within a cell through multiple facets of research. Advancements in proteomic methods have moved past the simple quantification of proteins to the identification of post-translational modifications (PTMs) and the ability to probe interactions between these proteins, spatially and temporally. Increased sensitivity and resolution of mass spectrometers and sample preparation protocols have drastically reduced the large amount of cells required and the experimental variability that had previously hindered its use in studying human neurological disorders. Proteomics offers a new perspective to study the altered molecular pathways and networks that are associated with autism spectrum disorders (ASD). The differences between the transcriptome and proteome, combined with the various types of post-translation modifications that regulate protein function and localization, highlight a novel level of research that has not been appropriately investigated. In this review, we will discuss strategies using proteomics to study ASD and other neurological disorders, with a focus on how these approaches can be combined with induced pluripotent stem cell (iPSC) studies. Proteomic analysis of iPSC-derived neurons have already been used to measure changes in the proteome caused by patient mutations, analyze changes in PTMs that resulted in altered biological pathways, and identify potential biomarkers. Further advancements in both proteomic techniques and human iPSC differentiation protocols will continue to push the field towards better understanding ASD disease pathophysiology. Proteomics using iPSC-derived neurons from individuals with ASD offers a window for observing the altered proteome, which is necessary in the future development of therapeutics against specific targets.

The Association Between Somatic Health, Autism Spectrum Disorder, and Autistic Traits

This study used a twin cohort to investigate the association of autism spectrum disorder (ASD) and autistic traits with somatic health. A total of 344 twins (172 pairs; mean age 15.56 ± 5.62 years) enriched for ASD and other neurodevelopmental conditions were examined. Medical history and current physical problems were collected with a validated questionnaire to determine twin’s somatic health. The Social Responsiveness Scale (SRS-2) was used to measure the participant’s severity of autistic traits. Identified somatic health issues with significant within-twin pair differences were tested in relation to both ASD diagnosis and autistic traits in a co-twin control model. Twins with ASD exhibited more neurological and immunological health problems compared to those without ASD (p = 0.005 and p = 0.004, respectively). The intra-pair differences of neurological conditions and SRS-2 score were significantly correlated in monozygotic twins differing for autism traits (r = 0.40, p = 0.001), while the correlation was not found for immunological problems. In addition, a conditional model for analysis of within-twin pair effects revealed an association between neurological problems and clinical ASD diagnosis (Odds ratio per neurological problem 3.15, p = 0.02), as well as autistic traits (β = 10.44, p = 0.006), after adjusting for possible effects of co-existing attention deficit hyperactivity disorder and general intellectual abilities. Our findings suggest that neurological problems are associated with autism, and that non-shared environmental factors contribute to the overlap for both clinical ASD and autistic traits. Further population-based twin studies are warranted to validate our results and examine in detailed the shared genetic and environmental contributions of neurological problems and ASD.

Multivariate Analysis of Plasma Metabolites in Children with Autism Spectrum Disorder and Gastrointestinal Symptoms Before and After Microbiota Transfer Therapy

Current diagnosis of autism spectrum disorder (ASD) is based on assessment of behavioral symptoms, although there is strong evidence that ASD affects multiple organ systems including the gastrointestinal (GI) tract. This study used Fisher discriminant analysis (FDA) to evaluate plasma metabolites from 18 children with ASD and chronic GI problems (ASD + GI cohort) and 20 typically developing (TD) children without GI problems (TD − GI cohort). Using three plasma metabolites that may represent three general groups of metabolic abnormalities, it was possible to distinguish the ASD + GI cohort from the TD − GI cohort with 94% sensitivity and 100% specificity after leave-one-out cross-validation. After the ASD + GI participants underwent Microbiota Transfer Therapy with significant improvement in GI and ASD-related symptoms, their metabolic profiles shifted significantly to become more similar to the TD − GI group, indicating potential utility of this combination of plasma metabolites as a biomarker for treatment efficacy. Two of the metabolites, sarcosine and inosine 5′-monophosphate, improved greatly after treatment. The third metabolite, tyramine O-sulfate, showed no change in median value, suggesting it and correlated metabolites to be a possible target for future therapies. Since it is unclear whether the observed differences are due to metabolic abnormalities associated with ASD or with GI symptoms (or contributions from both), future studies aiming to classify ASD should feature TD participants with GI symptoms and have larger sample sizes to improve confidence in the results.

Untargeted Metabolomics for Autism Spectrum Disorders: Current Status and Future Directions

Autism spectrum disorders (ASDs) are a group of neurodevelopment disorders characterized by childhood onset deficits in social communication and interaction. Although the exact etiology of most cases of ASDs is unknown, a portion has been proposed to be associated with various metabolic abnormalities including mitochondrial dysfunction, disorders of cholesterol metabolism, and folate abnormalities. Targeted biochemical testing like plasma amino acid and acylcarnitine profiles have demonstrated limited utility in helping to diagnose and manage such patients. Untargeted metabolomics has emerged, however, as a promising tool in screening for underlying biochemical abnormalities and managing treatment and as a means of investigating possible novel biomarkers for the disorder. Here, we review the principles and methodology behind untargeted metabolomics, recent pilot studies utilizing this technology, and areas in which it may be integrated into the care of children with this disorder in the future.